SIGCHI Outstanding Dissertation Award
Anna Maria Feit · 2019
Text input methods are an integral part of our daily interaction with digital devices. However, their design poses a complex problem: for any method, we must decide which input action (a button press, a hand gesture, etc.) produces which symbol (e.g., a character or word). With only 26 symbols and input actions, there are already more than 1026 distinct solutions, making it impossible to find the best one through manual design. Prior work has shown that we can use optimization methods to search such large design spaces efficiently and automatically find a good user interface with respect to the given objectives [6]. However, work in the text entry domain has been limited mostly to the performance optimization of (soft-)keyboards (see [2] for an overview). The Ph.D. thesis [2] advances the field of text-entry optimization by enlarging the space of optimizable text-input methods and proposing new criteria for assessing their optimality. Firstly, the design problem is formulated as an assignment problem for integer programming. This enables the use of standard mathematical solvers and algorithms for efficiently finding good solutions. Then, objective functions are developed, for assessing their optimality with respect to motor performance, ergonomics, and learnability. The corresponding models extend beyond interaction with soft keyboards, to consider multi-finger input, novel sensors, and alternative form factors. In addition, the thesis illustrates how to formulate models from prior work in terms of an assignment problem, providing a coherent theoretical basis for text entry optimization. The proposed objectives are applied in the optimization of three assignment problems: text input with multi-finger gestures in mid-air [8], text input on a long piano keyboard [4], and - for a contribution to the official French keyboard standard - input of special characters via a physical keyboard [3]. Combining the proposed models offers a multi-objective optimization approach able to capture the complex cognitive and motor processes during typing. . .